Project description:Dependent on concise, pre-defined protein sequence databases, traditional search algorithms perform poorly when analyzing mass spectra derived from wholly uncharacterized protein products. Conversely, de novo peptide sequencing algorithms can interpret mass spectra without relying on reference databases. However, such algorithms have been difficult to apply to complex protein mixtures, in part due to a lack of methods for automatically validating de novo sequencing results. Here, we present novel metrics for benchmarking de novo sequencing algorithm performance on large scale proteomics datasets, and present a method for accurately calibrating false discovery rates on de novo results. We also present a novel algorithm (LADS) which leverages experimentally disambiguated fragmentation spectra to boost sequencing accuracy and sensitivity. LADS improves sequencing accuracy on longer peptides relative to other algorithms and improves discriminability of correct and incorrect sequences. Using these advancements, we demonstrate accurate de novo identification of peptide sequences not identifiable using database search-based approaches.

2016-01-12 | PXD003317 | Pride

De novo assembly of siRNA immunity in wild plants

Project description:We describe an application of deep sequencing and de novo assembly of short RNA reads to investigate small interfering (si)RNAs mediated immunity in leaf samples from eight tree taxa naturally occurring in Wytham Woods, Oxfordshire, UK. BLAST search for homologues of contigs in the GenBank identified siRNA populations against a number of RNA viruses and a Ty1-copia retrotransposons in these tree species. Small RNA sequencing and de novo assembly

2012-06-01 | E-GEOD-22079 | biostudies-arrayexpress

pXg: Comprehensive identification of noncanonical MHC-I-associated peptides from de novo peptide sequencing using RNA-Seq reads

Project description:Discovering noncanonical peptides has been a common application of proteogenomics. Recent studies suggest that certain noncanonical peptides, known as ncMAPs (noncanonical MHC-I-associated peptides), that bind to major histocompatibility complex I may make good immunotherapeutic targets. De novo peptide sequencing is a great way to find ncMAPs since it can detect peptide sequences from their tandem mass spectra without using any sequence databases. However, this strategy hasn’t been widely applied for ncMAP identification because there is not a good way to estimate its false-positive rates. In order to completely and accurately identify immunopeptides using de novo peptide sequencing, we describe a unique pipeline called pXg. In contrast to current pipelines, it makes use of genomic data, RNA-Seq abundance and sequencing quality, in addition to proteomic features to increase the sensitivity and specificity of peptide identification. We show that the peptide-spectrum match quality and genetic traits have a clear relationship, showing that they can be utilized to evaluate peptide-spectrum matches. From ten samples, we found 24,449 cMAPs (canonical MHC-I-associated peptides) and 956 ncMAPs by using a target-decoy competition. 387 ncMAPs and 1,611 cMAPs were novel identifications that had not yet been published. We discovered 11 ncMAPs produced from a squirrel monkey retrovirus in human cell lines in addition to the 2 ncMAPs originating from a complementarity determining region 3 in an antibody thanks to the unrestricted search space assumed by de novo sequencing. These entirely new identifications show that pXg can make the most of de novo peptide sequencing's advantages and its potential use in the search for new immunotherapeutic targets.

2024-02-28 | PXD048006 | Pride

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data